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  • Chapter 1

    Artificial Intelligence

    1.1 Artificial Intelligence and Intelligence

    The goal of artificial intelligence is to try to develop computer programs, algorithms, and computer architectures that will behave very much like people and will do those things that in people would require intelligence, understanding, thinking, or reasoning. There are two important aspects to this study. First, there is the very grand goal of finding out how intelligence and human thinking works so that the same or similar methods can be made to work on a computer. This makes the subject on a par with physics where the goal is to understand how the whole universe of matter, energy, space, and time works. A second goal of AI is more modest: it is to produce computer programs that function more like people so that computers can be made more useful and so they can be made to do many things that people do and perhaps even faster and better than people can do them. These will be the problems that this book deals with, the grand aspect and the modest one.

    1.1.1 Intelligence

    To begin the consideration of artificial intelligence, it would be appropriate to start with some definition of intelligence. Unfortunately, giving a definition of intelligence that will satisfy everyone is not possible and there are critics who claim that there has been no in- telligence evident in artificial intelligence, only some modestly clever programming. Thus, to begin this book, we must briefly delay looking at the normal sort of material that would be found in the first chapter of a textbook and instead look first at the controversy that sur- rounds the definitions of intelligence and artificial intelligence. Looking at this debate will not settle the issues involved to everyone's satisfaction and readers will be left to form their own opinions about the nature of intelligence and artificial intelligence. To begin looking at the definition of intelligence, we will start with aspects of intelligence where there is no disagreement and then move on to the issues that are hotly debated.

    Everyone agrees that one aspect of human intelligence is the ability to respond cor- rectly to a novel situation. Furthermore, in giving intelligence tests where the goal is to solve problems, people who quickly give the correct answer will be judged as more intel- ligent than people who respond more slowly. Then on a long test, the "smarter" or more "intelligent" people will get more correct answers than less smart, less intelligent people. Within this process there is an important aspect to consider. In order to be able to respond correctly to a novel situation, the situation cannot be too novel. Thus, if the situation at

    1

  • Artificial Intelligence

    hand is to do some calculus problems, you cannot expect people who have never done any calculus to manage to respond at all. Familiarity with the subject area is necessary to be able to demonstrate intelligence. Knowledge gained by experience is essential. Then you can look (or be?) more intelligent in a certain area simply by having more experience with that area.

    The matter of possessing a certain amount of knowledge about a subject area can be quite subtle. For instance, adults ordinarily assume that it is easy to tell one person from the next simply by looking at them. It is assumed that adults have some kind of universal pattern recognition ability. However, it is often the case according to many media reports that when Americans visit some foreign country, especially, say, China, Americans often report that all the Chinese look the same. Of course, Chinese do not think that all Chinese look the same because native Chinese have had an extensive amount of experience recog- nizing Chinese faces. And to turn the tables, when Chinese students come to America they often report that all Americans look the same.1 Thus, even a "simple" task like recognizing faces is not some kind of universal ability thai adults develop but it is an ability that is de- veloped to work within their own specific environment and which will not work very well outside that environment.

    In addition to knowledge, speed, and experience, another key element of intelligence is the ability to learn. Everyone agrees that an intelligent system must be able to learn since obviously any person or program that cannot learn or which "mindlessly" keeps repeating a mistake over and over again will seem stupid. In fact, since as people learn a new task they get faster and faster at it, some people might require programs to get faster and faster as well.

    If intelligence consisted of only storing knowledge, doing pattern recognition, solving problems, and the ability to learn, then there would not be any problem in saying that programs can be intelligent. But there are other qualities that some critics believe are necessary for intelligence. Some of them are intuition, creativity, the ability to think, the ability to understand or to have consciousness, and feelings. Needless to say it is hard to pin down many of these vague quantities, but this has not stopped artificial intelligence researchers and critics of AI from debating the points ad inriniturn. Now we will mention some of the more prominent arguments.

    1.1.2 Thinking

    The issue of whether or not a machine could think might be decided quite easily by de- termining exactly how people think and then showing that the machine operates internally the same way or so close to the same way that there is no real difference between a hu- man thinker and a machine thinker. For instance, some AI researchers have proposed that thinking consists of manipulating large numbers of rules, so if that is all that a person does and the machine does the same thing, it too, should be regarded as thinking. Or, for an- other example, it has been suggested that thinking in people involves quantum mechanical processing. If this is the case, then an ordinary computer could not think but it is always possible that the right kind of quantum mechanical computer could think. Settling the issue this way may be simple, but it will be a long time before we know enough about human

    'This comes from nn informal survey by the author of Chinese students.

  • 1.1 Artificial Intelligence and Intelligence

    thinking to settle it this way. In the meantime, some people have proposed a weaker test for thinking: the Turing test.

    1.1.3 The Turing Test for Thinking

    Turing [238] and his followers believe that if a machine behaves very much like a person who is thinking, then the term thinking should apply to what the machine is doing as well. People who argue the validity of this test believe it is the running of an algorithm on a com- puter that constitutes thinking and it should not matter whether the computer is biological or electronic. This viewpoint is called the strong AI viewpoint. On the other hand, people who believe that electronic computing can only simulate thinking are said to have the weak AI viewpoint.

    The most common version of the Turing test is the following (for Turing's original version, see Exercise 1.1): Put a person or a sophisticated computer program designed to simulate a person in a closed room. Give another person a teletype connection to the room and let this person interrogate the occupant of the closed room. The interrogator may ask the occupant any sort of question, including such questions as, "Are you human?" "Tell me about your childhood." "Is it warm in the room?" "How much is 1087567898 times 176568321?" In this last question a digital computer has a decided advantage over a human being in terms of speed and accuracy so that the designers of the simulated human being must come up with a way to make it as slow and unreliable as people are at doing arithmetic. In the case of "Are you human?" the machine must be prepared to lie. It is given, of course, that if the occupant of the sealed room is a person, the person is thinking. If after a short period of time the questioner could be fooled into thinking that the occupant was a person when it actually was a machine, it should be fair to say that the machine must also be thinking.

    With a sufficiently complex computer and computer program, it would be a virtual cer- tainty that many naive questioners will be unable to determine after a short period of time whether or not the occupant of the sealed room is a human being or a machine simulating a human being. However, it also seems a virtual certainty that more determined and sophis- ticated questioners will find ways to tell the difference between a machine and a human being in the sealed room (for instance see Exercise 1.1).

    Notice also that the Turing test is relatively weak in that to a large extent it is a test of knowledge: if a computer failed to pass the Turing test because it did not know something that a human being should know it is no reason to claim that it is not thinking! Thinking is something that is independent of knowledge.

    1.1.4 The Chinese Room Argument

    An important argument against the strong AI viewpoint is the Chinese room argument of Searle [196, 197], In this thought experiment the occupant of the Turing test room has to communicate in Chinese with the interrogator and Searle modifies the Turing test in the following way. Searle goes into the closed room to answer questions given to him despite the fact that he does not know any Chinese. He takes with him into the room a book with a Chinese understanding algorithm in it plus some scratch paper on which to do calculations. Searle takes input on little sheets of paper, consults the book that contains the algorithm for

  • Artificial Intelligence

    understanding Chinese, and by following its directions he prod

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